metaSEM (version 1.2.5.1)

vcov: Extract Covariance Matrix Parameter Estimates from Objects of Various Classes

Description

It extracts the variance-covariance matrix of the parameter estimates from objects of various classes.

Usage

# S3 method for tssem1FEM
vcov(object, ...)
# S3 method for tssem1FEM.cluster
vcov(object, ...)
# S3 method for tssem1REM
vcov(object, select = c("all", "fixed", "random"), robust=FALSE, ...)
# S3 method for wls
vcov(object, ...)
# S3 method for wls.cluster
vcov(object, ...)
# S3 method for meta
vcov(object, select = c("all", "fixed", "random"), robust=FALSE, ...)
# S3 method for meta3X
vcov(object, select = c("all", "fixed", "random","allX"), robust=FALSE, ...)
# S3 method for reml
vcov(object, ...)
# S3 method for MxRAMModel
vcov(object, ...)
# S3 method for osmasem
vcov(object, select=c("fixed", "all", "random"), robust=FALSE, ...)

Value

A variance-covariance matrix of the parameter estimates.

Arguments

object

An object returned from objects of various classes

select

Select all for both fixed- and random-effects parameters, fixed for the fixed-effects parameters or random for the random-effects parameters. For meta3X objects, allX is used to extract all parameters including the predictors and auxiliary variables.

robust

Logicial. Whether to use robust standard error from imxRobustSE.

...

Further arguments; currently none is used

Author

Mike W.-L. Cheung <[e-mail]>

See Also

tssem1, wls, meta, reml

Examples

## Random-effects meta-analysis
model1 <- meta(y=yi, v=vi, data=Hox02)
vcov(model1)

## Fixed-effects only
vcov(model1, select="fixed")

## Random-effects only
vcov(model1, select="random")